Experienced Data Scientist – Data Security

At Thales, we know technology has the ability to make our world more secure, sustainable, and inclusive – and that it’s all driven by human intelligence.

Because it takes human intelligence to build and power the systems and solutions that people depend on every day. So we stay curious and make space for diverse points of view. We share what we know and we challenge what’s possible.

We’re driving progress in some of the world’s most important industries - from the bottom of the oceans to the depths of space and cyberspace - and from manufacturing to engineering, we work together to build a future we can all trust.

Imperva, a Thales company, is a globally recognized cybersecurity leader, dedicated to securing data and applications across diverse environments. Our cutting-edge solutions empower organizations to safeguard their most critical assets, ensuring robust protection against emerging threats.

Imperva, a Thales company and a leader in Application & Data Security, is looking for an Experienced Data Scientist to join our Threat Research group and build production-grade AI systems focused on NLP, LLMs, and sensitive data classification.

We are looking for an Experienced Data Scientist – Data Security.

This role combines hands-on research, large-scale production systems, and close collaboration with engineering teams. The work focuses on solving real-world cybersecurity and data security challenges using modern AI approaches, including document understanding, semantic classification, LLM pipelines, and compound AI systems.

About the Team:

Our Threat Research group is composed of elite researchers and developers. We research applications, DDoS, and database attacks, develop algorithms for products, and drive innovation and thought leadership in cybersecurity. The team also develops advanced AI-driven capabilities for Data Security use cases, operating at large production scale across enterprise environments.

Key Responsibilities:

• Design and develop NLP and LLM-based solutions for document understanding and sensitive data classification.
• Drive projects from research and prototyping to production deployment.
• Work closely with engineering teams to integrate and promote models within large-scale ML pipelines.
• Improve model quality, scalability, latency, and reliability.
• Design evaluation and monitoring frameworks for production AI systems.
• Ensure AI models are reliable, scalable, and production-ready for enterprise security environments.
  
  

• 5+ years of experience in Data Science / Applied ML, with strong hands-on experience building and deploying NLP and LLM-based solutions in production environments.
• Experience in Data Security or Cyber Security is a strong advantage, particularly in areas such as document classification, semantic search, or enterprise data analysis.
• Strong Python skills and experience with modern ML/DL frameworks such as PyTorch or TensorFlow, including transformer architectures and fine-tuning workflows.
• Experience working with large-scale datasets and production ML systems, including tools such as SQL, Spark, or similar distributed data processing frameworks.
• Experience with MLOps, scalable model deployment, inference optimization, CI/CD practices, and the end-to-end ML lifecycle from data preparation to production monitoring.
• Experience working closely with software engineering teams in cloud-native environments; familiarity with AWS/Azure/GCP, Kubernetes, and microservices architectures is a plus.
• Track record of delivering impactful AI solutions in real-world production settings, with strong communication, collaboration, and independent problem-solving skills.
• Ph.D. or M.Sc. in Computer Science, Engineering, Mathematics, or a related quantitative field is a plus, but not required with equivalent industry experience.